| --- |
| language: |
| - ko |
| tags: |
| - ocr |
| - document-understanding |
| - korean |
| - benchmark |
| size_categories: |
| - n<10K |
| pretty_name: KDoc-OCRBench |
| extra_gated_heading: KDoc-OCRBench Access Request |
| extra_gated_description: >- |
| This dataset contains real-world Korean industrial documents and is not |
| openly redistributable. Access is granted on a case-by-case basis for |
| research and evaluation purposes only. Please fill in the information below |
| to request access. |
| extra_gated_fields: |
| Full Name: text |
| Company/Organization: text |
| Email: text |
| Intended Use (evaluation / research / other): text |
| I agree not to redistribute this dataset: checkbox |
| extra_gated_button_content: Request access |
| --- |
| |
| # KDoc-OCRBench (Korean Document OCR Benchmark) |
|
|
| The first comprehensive Korean document OCR benchmark developed by [ONTHEIT](http://www.ontheit.com/). |
|
|
| **14,738 test cases across 804 Korean PDFs in 7 industrial document categories** — designed to fill the gap in standardized Korean OCR evaluation. |
|
|
| Existing OCR benchmarks are primarily English-focused, making it difficult to evaluate model performance on Korean documents. KDoc-OCRBench addresses this gap with real-world Korean documents spanning contracts, medical records, financial forms, logistics paperwork, educational materials, government documents, and presentation slides. |
|
|
| ## Overview |
|
|
| - **804 Korean PDFs** across 7 document categories |
| - **14,738 unit-test-style assertions** covering text presence, text absence, table structure, and baseline quality |
| - Based on the [olmOCR-bench](https://huggingface.co/datasets/allenai/olmOCR-bench) methodology by Allen AI — each test is a focused assertion (e.g., "this text must appear", "this cell must be to the right of that cell") rather than a full-text comparison, making evaluation robust to formatting differences between models |
| - Korean-specific normalization for decorative spacing and multi-line table cells |
|
|
| ## Dataset Structure |
|
|
| ``` |
| KDoc-OCRBench/ |
| ├── pdfs/ # 804 PDF documents organized by category |
| │ ├── CorporateDocs/ |
| │ ├── EducationalDocs/ |
| │ ├── FinancialInsuranceDocs/ |
| │ ├── LogisticsDocs/ |
| │ ├── MedicalDocs/ |
| │ ├── PresentationSlides/ |
| │ └── PublicDocs/ |
| ├── long_tests.jsonl # Text presence/absence tests (10,137) |
| ├── table_tests.jsonl # Table structure tests (4,147) |
| └── header_footer_tests.jsonl # Header/footer tests (454) |
| ``` |
|
|
| ## Test Types |
|
|
| | Type | Count | Description | |
| |------|------:|-------------| |
| | Text Presence (`present`) | 10,137 | Verifies specific Korean text appears in the output (with optional fuzzy matching) | |
| | Text Absence (`absent`) | 454 | Verifies certain text (e.g., page headers/footers) is NOT in the output | |
| | Table (`table`) | 4,147 | Validates table cell content and spatial relationships (up/down/left/right neighbors, column/row headings) | |
| | Baseline | 804 | Checks output is non-empty, not repeating, and contains valid characters (one per PDF) | |
|
|
| ## Document Categories |
|
|
| ### CorporateDocs (124 documents) |
| Corporate documents — employment contracts, service performance certificates, business plans, internal reports, meeting minutes, and more. |
|
|
| ### EducationalDocs (158 documents) |
| Educational documents — preventive education materials, student residence surveys, curriculum guides, school support procedures, admission assignment notices, academic transcripts, and more. |
|
|
| ### FinancialInsuranceDocs (64 documents) |
| Financial and insurance documents — securities issuance terms, payment notices, income deduction statements, credit transaction agreements, automatic transfer applications, insurance claim forms, and more. |
|
|
| ### LogisticsDocs (72 documents) |
| Logistics documents — simplified customs declarations, price declarations, import customs clearance guides, goods requisitions, transaction statements, multimodal bills of lading, and more. |
|
|
| ### MedicalDocs (118 documents) |
| Medical documents — medical records, medical opinions, diagnostic certificates, prescriptions, health checkup result notices, symptom and treatment records, medical fee receipts, and more. |
|
|
| ### PresentationSlides (99 documents) |
| Presentation materials — major initiative progress and plans, social investment materials, social impact reports, collaboration strategy decks, and more. |
|
|
| ### PublicDocs (169 documents) |
| Public documents — initial salary grade determination procedures, employment support program guides, performance indicator and weighting specifications, name change applications, leak detection reports, and more. |
|
|
| ## Benchmark Results |
|
|
| See the leaderboard and evaluation code at [ONTHEIT-AI/BizOnAI-OCR](https://github.com/ONTHEIT-AI/BizOnAI-OCR). |
|
|
| ## Credits |
|
|
| - Korean document data collected and labeled by [ONTHEIT](http://www.ontheit.com/) |
| - Evaluation methodology inspired by [olmOCR-bench](https://huggingface.co/datasets/allenai/olmOCR-bench) by Allen AI |
|
|
| ## License & Access |
|
|
| This dataset contains real-world Korean industrial documents and is **not openly redistributable**. Access is granted on a case-by-case basis for research and evaluation purposes. |
|
|
| To request access, contact [ONTHEIT](http://www.ontheit.com/) at **bizonai@ontheit.com**. Granted users may use the dataset only for OCR evaluation and may not redistribute it. |
|
|
